Cranial growth in isolated sagittal craniosynostosis compared with normal growth in the first 6 months of age
Sagittal craniosynostosis (SCS), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive surgery to correct. It is important to find objective and repeatable measures of severity and surgical outcome to examine the effect of timing an...
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Published in | Journal of anatomy Vol. 236; no. 1; pp. 105 - 116 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
England
Wiley Subscription Services, Inc
01.01.2020
John Wiley and Sons Inc |
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Online Access | Get full text |
ISSN | 0021-8782 1469-7580 1469-7580 |
DOI | 10.1111/joa.13085 |
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Abstract | Sagittal craniosynostosis (SCS), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive surgery to correct. It is important to find objective and repeatable measures of severity and surgical outcome to examine the effect of timing and technique on different SCS surgeries. The purpose of this study was to develop statistical models of infant (0–6 months old) skull growth in both normative and SCS subjects (prior to surgery). Our goal was to apply these models to the assessment of differences between these two groups in overall post‐natal growth patterns and sutural growth rates as a first step to develop methods for predictive models of surgical outcome. We identified 81 patients with isolated, non‐syndromic SCS from Seattle Children's Craniofacial Center patient database who had a preoperative CT exam before the age of 6 months. As a control group, we identified 117 CT exams without any craniofacial abnormalities or bone fractures in the same age group. We first created population‐level templates from the CT images of the SCS and normal groups. All CT images from both groups, as well as the canonical templates of both cohorts, were annotated with anatomical landmarks, which were used in a growth model that predicted the locations of these landmarks at a given age based on each population. Using the template images and the landmark positions predicted by the growth models, we created 3D meshes for each week of age up to 6 months for both populations. To analyze the growth patterns at the suture sites, we annotated both templates with additional semi‐landmarks equally spaced along the metopic, coronal, sagittal and lambdoidal cranial sutures. By transferring these semi‐landmarks to meshes produced from the growth model, we measured the displacement of the bone borders and suture closure rates. We found that the growth at the metopic and coronal sutures were more rapid in the SCS cohort than in the normal cohort. The antero‐posterior displacement of the semi‐landmarks also indicated a more rapid growth in the sagittal plane in the SCS model than in the normal model. Statistical templates and geometric morphometrics are promising tools for understanding the growth patterns in normal and synostotic populations and to produce objective and reproducible measurements of severity and outcome. Our study is the first of its kind to quantify the bone growth for the first 6 months of life in both normal and sagittal synostosis patients.
Normal growth vs. growth in sagittal craniosynostosis. (A) Mediolateral displacement: positive values indicate medial movement (can be interpreted as suture closure) and negative values indicate lateral movement (mostly associated with the overall growth of the skull). (B) Superoinferior displacement: positive values indicate a superior movement. (C) Anteroposterior displacement: positive values indicate anterior, and negative values indicate posterior movement with respect to basion. |
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AbstractList | Sagittal craniosynostosis (SCS), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive surgery to correct. It is important to find objective and repeatable measures of severity and surgical outcome to examine the effect of timing and technique on different SCS surgeries. The purpose of this study was to develop statistical models of infant (0-6 months old) skull growth in both normative and SCS subjects (prior to surgery). Our goal was to apply these models to the assessment of differences between these two groups in overall post-natal growth patterns and sutural growth rates as a first step to develop methods for predictive models of surgical outcome. We identified 81 patients with isolated, non-syndromic SCS from Seattle Children's Craniofacial Center patient database who had a preoperative CT exam before the age of 6 months. As a control group, we identified 117 CT exams without any craniofacial abnormalities or bone fractures in the same age group. We first created population-level templates from the CT images of the SCS and normal groups. All CT images from both groups, as well as the canonical templates of both cohorts, were annotated with anatomical landmarks, which were used in a growth model that predicted the locations of these landmarks at a given age based on each population. Using the template images and the landmark positions predicted by the growth models, we created 3D meshes for each week of age up to 6 months for both populations. To analyze the growth patterns at the suture sites, we annotated both templates with additional semi-landmarks equally spaced along the metopic, coronal, sagittal and lambdoidal cranial sutures. By transferring these semi-landmarks to meshes produced from the growth model, we measured the displacement of the bone borders and suture closure rates. We found that the growth at the metopic and coronal sutures were more rapid in the SCS cohort than in the normal cohort. The antero-posterior displacement of the semi-landmarks also indicated a more rapid growth in the sagittal plane in the SCS model than in the normal model. Statistical templates and geometric morphometrics are promising tools for understanding the growth patterns in normal and synostotic populations and to produce objective and reproducible measurements of severity and outcome. Our study is the first of its kind to quantify the bone growth for the first 6 months of life in both normal and sagittal synostosis patients. Sagittal craniosynostosis (SCS), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive surgery to correct. It is important to find objective and repeatable measures of severity and surgical outcome to examine the effect of timing and technique on different SCS surgeries. The purpose of this study was to develop statistical models of infant (0–6 months old) skull growth in both normative and SCS subjects (prior to surgery). Our goal was to apply these models to the assessment of differences between these two groups in overall post‐natal growth patterns and sutural growth rates as a first step to develop methods for predictive models of surgical outcome. We identified 81 patients with isolated, non‐syndromic SCS from Seattle Children's Craniofacial Center patient database who had a preoperative CT exam before the age of 6 months. As a control group, we identified 117 CT exams without any craniofacial abnormalities or bone fractures in the same age group. We first created population‐level templates from the CT images of the SCS and normal groups. All CT images from both groups, as well as the canonical templates of both cohorts, were annotated with anatomical landmarks, which were used in a growth model that predicted the locations of these landmarks at a given age based on each population. Using the template images and the landmark positions predicted by the growth models, we created 3D meshes for each week of age up to 6 months for both populations. To analyze the growth patterns at the suture sites, we annotated both templates with additional semi‐landmarks equally spaced along the metopic, coronal, sagittal and lambdoidal cranial sutures. By transferring these semi‐landmarks to meshes produced from the growth model, we measured the displacement of the bone borders and suture closure rates. We found that the growth at the metopic and coronal sutures were more rapid in the SCS cohort than in the normal cohort. The antero‐posterior displacement of the semi‐landmarks also indicated a more rapid growth in the sagittal plane in the SCS model than in the normal model. Statistical templates and geometric morphometrics are promising tools for understanding the growth patterns in normal and synostotic populations and to produce objective and reproducible measurements of severity and outcome. Our study is the first of its kind to quantify the bone growth for the first 6 months of life in both normal and sagittal synostosis patients. Normal growth vs. growth in sagittal craniosynostosis. (A) Mediolateral displacement: positive values indicate medial movement (can be interpreted as suture closure) and negative values indicate lateral movement (mostly associated with the overall growth of the skull). (B) Superoinferior displacement: positive values indicate a superior movement. (C) Anteroposterior displacement: positive values indicate anterior, and negative values indicate posterior movement with respect to basion. Sagittal craniosynostosis (SCS), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive surgery to correct. It is important to find objective and repeatable measures of severity and surgical outcome to examine the effect of timing and technique on different SCS surgeries. The purpose of this study was to develop statistical models of infant (0–6 months old) skull growth in both normative and SCS subjects (prior to surgery). Our goal was to apply these models to the assessment of differences between these two groups in overall post‐natal growth patterns and sutural growth rates as a first step to develop methods for predictive models of surgical outcome. We identified 81 patients with isolated, non‐syndromic SCS from Seattle Children's Craniofacial Center patient database who had a preoperative CT exam before the age of 6 months. As a control group, we identified 117 CT exams without any craniofacial abnormalities or bone fractures in the same age group. We first created population‐level templates from the CT images of the SCS and normal groups. All CT images from both groups, as well as the canonical templates of both cohorts, were annotated with anatomical landmarks, which were used in a growth model that predicted the locations of these landmarks at a given age based on each population. Using the template images and the landmark positions predicted by the growth models, we created 3D meshes for each week of age up to 6 months for both populations. To analyze the growth patterns at the suture sites, we annotated both templates with additional semi‐landmarks equally spaced along the metopic, coronal, sagittal and lambdoidal cranial sutures. By transferring these semi‐landmarks to meshes produced from the growth model, we measured the displacement of the bone borders and suture closure rates. We found that the growth at the metopic and coronal sutures were more rapid in the SCS cohort than in the normal cohort. The antero‐posterior displacement of the semi‐landmarks also indicated a more rapid growth in the sagittal plane in the SCS model than in the normal model. Statistical templates and geometric morphometrics are promising tools for understanding the growth patterns in normal and synostotic populations and to produce objective and reproducible measurements of severity and outcome. Our study is the first of its kind to quantify the bone growth for the first 6 months of life in both normal and sagittal synostosis patients. Sagittal craniosynostosis ( SCS ), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive surgery to correct. It is important to find objective and repeatable measures of severity and surgical outcome to examine the effect of timing and technique on different SCS surgeries. The purpose of this study was to develop statistical models of infant (0–6 months old) skull growth in both normative and SCS subjects (prior to surgery). Our goal was to apply these models to the assessment of differences between these two groups in overall post‐natal growth patterns and sutural growth rates as a first step to develop methods for predictive models of surgical outcome. We identified 81 patients with isolated, non‐syndromic SCS from Seattle Children's Craniofacial Center patient database who had a preoperative CT exam before the age of 6 months. As a control group, we identified 117 CT exams without any craniofacial abnormalities or bone fractures in the same age group. We first created population‐level templates from the CT images of the SCS and normal groups. All CT images from both groups, as well as the canonical templates of both cohorts, were annotated with anatomical landmarks, which were used in a growth model that predicted the locations of these landmarks at a given age based on each population. Using the template images and the landmark positions predicted by the growth models, we created 3D meshes for each week of age up to 6 months for both populations. To analyze the growth patterns at the suture sites, we annotated both templates with additional semi‐landmarks equally spaced along the metopic, coronal, sagittal and lambdoidal cranial sutures. By transferring these semi‐landmarks to meshes produced from the growth model, we measured the displacement of the bone borders and suture closure rates. We found that the growth at the metopic and coronal sutures were more rapid in the SCS cohort than in the normal cohort. The antero‐posterior displacement of the semi‐landmarks also indicated a more rapid growth in the sagittal plane in the SCS model than in the normal model. Statistical templates and geometric morphometrics are promising tools for understanding the growth patterns in normal and synostotic populations and to produce objective and reproducible measurements of severity and outcome. Our study is the first of its kind to quantify the bone growth for the first 6 months of life in both normal and sagittal synostosis patients. Sagittal craniosynostosis (SCS), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive surgery to correct. It is important to find objective and repeatable measures of severity and surgical outcome to examine the effect of timing and technique on different SCS surgeries. The purpose of this study was to develop statistical models of infant (0–6 months old) skull growth in both normative and SCS subjects (prior to surgery). Our goal was to apply these models to the assessment of differences between these two groups in overall post‐natal growth patterns and sutural growth rates as a first step to develop methods for predictive models of surgical outcome. We identified 81 patients with isolated, non‐syndromic SCS from Seattle Children's Craniofacial Center patient database who had a preoperative CT exam before the age of 6 months. As a control group, we identified 117 CT exams without any craniofacial abnormalities or bone fractures in the same age group. We first created population‐level templates from the CT images of the SCS and normal groups. All CT images from both groups, as well as the canonical templates of both cohorts, were annotated with anatomical landmarks, which were used in a growth model that predicted the locations of these landmarks at a given age based on each population. Using the template images and the landmark positions predicted by the growth models, we created 3D meshes for each week of age up to 6 months for both populations. To analyze the growth patterns at the suture sites, we annotated both templates with additional semi‐landmarks equally spaced along the metopic, coronal, sagittal and lambdoidal cranial sutures. By transferring these semi‐landmarks to meshes produced from the growth model, we measured the displacement of the bone borders and suture closure rates. We found that the growth at the metopic and coronal sutures were more rapid in the SCS cohort than in the normal cohort. The antero‐posterior displacement of the semi‐landmarks also indicated a more rapid growth in the sagittal plane in the SCS model than in the normal model. Statistical templates and geometric morphometrics are promising tools for understanding the growth patterns in normal and synostotic populations and to produce objective and reproducible measurements of severity and outcome. Our study is the first of its kind to quantify the bone growth for the first 6 months of life in both normal and sagittal synostosis patients. Normal growth vs. growth in sagittal craniosynostosis. (A) Mediolateral displacement: positive values indicate medial movement (can be interpreted as suture closure) and negative values indicate lateral movement (mostly associated with the overall growth of the skull). (B) Superoinferior displacement: positive values indicate a superior movement. (C) Anteroposterior displacement: positive values indicate anterior, and negative values indicate posterior movement with respect to basion. Sagittal craniosynostosis (SCS), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive surgery to correct. It is important to find objective and repeatable measures of severity and surgical outcome to examine the effect of timing and technique on different SCS surgeries. The purpose of this study was to develop statistical models of infant (0-6 months old) skull growth in both normative and SCS subjects (prior to surgery). Our goal was to apply these models to the assessment of differences between these two groups in overall post-natal growth patterns and sutural growth rates as a first step to develop methods for predictive models of surgical outcome. We identified 81 patients with isolated, non-syndromic SCS from Seattle Children's Craniofacial Center patient database who had a preoperative CT exam before the age of 6 months. As a control group, we identified 117 CT exams without any craniofacial abnormalities or bone fractures in the same age group. We first created population-level templates from the CT images of the SCS and normal groups. All CT images from both groups, as well as the canonical templates of both cohorts, were annotated with anatomical landmarks, which were used in a growth model that predicted the locations of these landmarks at a given age based on each population. Using the template images and the landmark positions predicted by the growth models, we created 3D meshes for each week of age up to 6 months for both populations. To analyze the growth patterns at the suture sites, we annotated both templates with additional semi-landmarks equally spaced along the metopic, coronal, sagittal and lambdoidal cranial sutures. By transferring these semi-landmarks to meshes produced from the growth model, we measured the displacement of the bone borders and suture closure rates. We found that the growth at the metopic and coronal sutures were more rapid in the SCS cohort than in the normal cohort. The antero-posterior displacement of the semi-landmarks also indicated a more rapid growth in the sagittal plane in the SCS model than in the normal model. Statistical templates and geometric morphometrics are promising tools for understanding the growth patterns in normal and synostotic populations and to produce objective and reproducible measurements of severity and outcome. Our study is the first of its kind to quantify the bone growth for the first 6 months of life in both normal and sagittal synostosis patients.Sagittal craniosynostosis (SCS), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive surgery to correct. It is important to find objective and repeatable measures of severity and surgical outcome to examine the effect of timing and technique on different SCS surgeries. The purpose of this study was to develop statistical models of infant (0-6 months old) skull growth in both normative and SCS subjects (prior to surgery). Our goal was to apply these models to the assessment of differences between these two groups in overall post-natal growth patterns and sutural growth rates as a first step to develop methods for predictive models of surgical outcome. We identified 81 patients with isolated, non-syndromic SCS from Seattle Children's Craniofacial Center patient database who had a preoperative CT exam before the age of 6 months. As a control group, we identified 117 CT exams without any craniofacial abnormalities or bone fractures in the same age group. We first created population-level templates from the CT images of the SCS and normal groups. All CT images from both groups, as well as the canonical templates of both cohorts, were annotated with anatomical landmarks, which were used in a growth model that predicted the locations of these landmarks at a given age based on each population. Using the template images and the landmark positions predicted by the growth models, we created 3D meshes for each week of age up to 6 months for both populations. To analyze the growth patterns at the suture sites, we annotated both templates with additional semi-landmarks equally spaced along the metopic, coronal, sagittal and lambdoidal cranial sutures. By transferring these semi-landmarks to meshes produced from the growth model, we measured the displacement of the bone borders and suture closure rates. We found that the growth at the metopic and coronal sutures were more rapid in the SCS cohort than in the normal cohort. The antero-posterior displacement of the semi-landmarks also indicated a more rapid growth in the sagittal plane in the SCS model than in the normal model. Statistical templates and geometric morphometrics are promising tools for understanding the growth patterns in normal and synostotic populations and to produce objective and reproducible measurements of severity and outcome. Our study is the first of its kind to quantify the bone growth for the first 6 months of life in both normal and sagittal synostosis patients. |
Author | Mercan, Ezgi Hopper, Richard A. Maga, A. Murat |
AuthorAffiliation | 1 Craniofacial Center Seattle Children's Hospital Seattle WA USA 4 Seattle Children's Research Institute Center for Developmental Biology and Regenerative Medicine Seattle WA USA 2 Division of Plastic Surgery Department of Surgery University of Washington Seattle WA USA 3 Department of Pediatrics Division of Craniofacial Medicine University of Washington Seattle WA USA |
AuthorAffiliation_xml | – name: 4 Seattle Children's Research Institute Center for Developmental Biology and Regenerative Medicine Seattle WA USA – name: 3 Department of Pediatrics Division of Craniofacial Medicine University of Washington Seattle WA USA – name: 1 Craniofacial Center Seattle Children's Hospital Seattle WA USA – name: 2 Division of Plastic Surgery Department of Surgery University of Washington Seattle WA USA |
Author_xml | – sequence: 1 givenname: Ezgi surname: Mercan fullname: Mercan, Ezgi organization: Seattle Children's Hospital – sequence: 2 givenname: Richard A. surname: Hopper fullname: Hopper, Richard A. organization: University of Washington – sequence: 3 givenname: A. Murat orcidid: 0000-0002-7921-9018 surname: Maga fullname: Maga, A. Murat email: maga@uw.edu organization: University of Washington |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31691965$$D View this record in MEDLINE/PubMed |
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Snippet | Sagittal craniosynostosis (SCS), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive... Sagittal craniosynostosis ( SCS ), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive... |
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SubjectTerms | Age Bone growth Cranial sutures Cranial Sutures - diagnostic imaging Cranial Sutures - growth & development Craniosynostoses - diagnostic imaging Craniosynostosis Dysostosis Female Fractures geometric morphometrics Growth models Growth patterns Growth rate Humans Imaging, Three-Dimensional Infant Infant, Newborn Male Mathematical models Methods morphometrics Morphometry Original Prediction models shape modeling Skull Skull - diagnostic imaging Skull - growth & development Statistical analysis Surgery Surgical mesh Surgical outcomes Tomography, X-Ray Computed |
Title | Cranial growth in isolated sagittal craniosynostosis compared with normal growth in the first 6 months of age |
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